The perception of depth from stereoscopic images was illustrated centuries ago with stereoscopic drawings. Such technology entered the photographic age in 1838, following a description by Charles Wheatstone to the Royal Scottish Society of Arts. Stereoscopic images are formed by two two-dimensional (2D) images of a single scene taken from slightly different perspectives. These two slightly different images are analogous to the slightly different views from the left and right eyes of a human viewer. The illusion of depth by a three-dimensional (3D) image from two 2D images is produced when the “left” image of the stereoscopic pair of images is processed by the viewer's left eye only and the “right” image is processed by the viewer's right eye.
A variety of 3D image display apparatuses have been developed over the centuries for the separation and discrete transmission of left and right stereoscopic images to the appropriate eyes of the viewer. Examples of such stereoscopic display apparatuses include color-separation anaglyph filters, polarizing filters, wavelength-multiplexing INFITEC filters and time-sequential LCD shutter glasses. Most of these apparatuses suffer from ghosting artifacts that result from information leakage, often referred to as “crosstalk”, between one perspective view of the stereoscopic pair to the other view (e.g. from the left eye to the right eye or from the right eye to the left eye). Because of ghosting, the left eye of a viewer sees a portion of information from the right eye image in addition to the appropriate left eye image, and vice versa. Ghosting in 3D images can compromise the image quality of a stereoscopic 3D display. While stereoscopic display apparatuses deliver 3D effects, most cannot eliminate crosstalk and thus cannot deliver ghosting-free 3D images. Furthermore, current efforts that seek to eliminate crosstalk in display devices are difficult and costly. In one approach, for example, two separating techniques are used at the same time, such as using polarization and shutter glasses, which provides significant reduction in ghosting. However, the economics of setting up and maintaining such a system becomes too costly in a very competitive commercial cinema market.
Cinema presentations are changing from film based projection to projecting from a digital storage medium. For 3D presentations that experience ghosting, it is now possible to manipulate image content on a pixel-by-pixel basis. This aspect can be used to reduce ghosting in digitally projected stereoscopic presentations. Digital image processing techniques, for example, have been developed that seek to reduce ghosting by modifying image data. Examples of these methods include reducing ghosting by subtracting ghosting artifacts from images and reducing ghosting by changing the brightness of an image to facilitate ghosting artifact subtraction. Additional examples follow.
G. Street (EP 0819359) describes a method to enhance stereoscopic display quality by reconditioning each channel via an inverted crosstalk matrix to cancel the crosstalk. The method accounts for the viewer's location. The matrix is a simple optical crosstalk model and can subtract ghosting from each eye's image. To make the matrix always solvable, an overall neutral bias is imposed. However, measuring parameters of the model can be difficult.
Sebastien Weitbruch (EP 1460857) describes a method of compensating for ghosting images in time sequential stereoscopic images where crosstalk is produced in a system by phosphor lag. The method seeks to withdraw the percentage of crosstalk in an image from the original image and, where the original image level was zero (0), globally adds a maximum level of the ghosting image to hide the ghosting. The method is limited by a resulting loss of contrast of the whole image or compromised by allowing a certain amount of ghosting.
James Libscomb, Tomas Watson and Wayne Wooten, “Reducing crosstalk between stereoscopic views,” in Stereoscopic Displays and Virtual Reality Systems IX, Proceedings of SPIE Vol. 2177, pp. 92-96 (February 1994) describes a method of reducing crosstalk by globally boosting a dark background to a grey level, compressing the image's dynamic range and then subtracting a predefined crosstalk from the other image of the stereoscopic pair. However, the methods are heuristic and inapplicable to complicated images as it may be limited to artificial representation images.
Janusz Konrad “Cancellation of image crosstalk in time-sequential displays of stereoscopic video,” in IEEE Transactions on Image Processing, Vol. 9, No. 5, pp 897-908 (May 2000) describes a method for conducting psychovisual calibration by defining a human psychovisual model in a set of mapping LUTs. By brute force, the model maps the original image to a processed image. The method may produce a highly distorted image even though ghosting is alleviated. The calibration process uses limited psychovisual sampling points and is dependent on specified 3D system physical characteristics. Furthermore, the method does not separate psychovisual effects from system characteristics. The system, by its nature, has low accuracy and does not allow for automatic use.
Manly Cain “Improving 3D Anaglyphs Through Image Processing,” http://www.rmcain.com/pageserver.mv?MCAMA3DUpdate (copyright 1999) describes a method for reducing ghosting by adjusting the z-axis distance to achieve a minimum ghosting level while retaining the original relative depth. The method is, however, heuristic and fully manual. In addition, changing z-axis distance may not be possible in all circumstances or applications.
Cowan et al. (U.S. Patent Pub. No. 2006/0268104) describes a ghosting compensation method and system for improving stereoscopic projection. The method and system divides the projection screen into a plurality of regions, each with a potentially different ghosting profile. A simple model is used to estimate possible ghosting from an image of one eye and subtract it from the original image. Human psychovisual factors are ignored and, therefore, the method and system may not be effective or may otherwise result in undesirable artifacts, especially in a multiple view environment. Furthermore, no content-based local ghosting removal operations are performed.
Brian Guralnick (U.S. Pat. No. 6,532,008) describes a user interactive software environment in which the user may manually eliminate ghosting effects through a graphical user interface (GUI) and image editor and composer methods. A simulation and evaluation apparatus is described. The ghosting reduction process is a combination of selected positive percentages and negative percentages of the original images. In cases where final images are negative, a percentage of white is added globally.
S. Klimenko “Crosstalk reduction in passive stereo-projection systems,” EUROGRAPHICS 2003 describes a method for the reduction of crosstalk in a passive stereo-projection system. This method involves the subtraction of a proportion of leakage in one eye image from the other eye image. If necessary, a constant amount of color is added to the image. The method potentially results in an undesirably bright background area in images.
Other Related References include: John Ross et al., “Contrast Adaptation and Contrast Masking in Human Vision,” Speed Proceedings: Biological Sciences, Vol. 246, No. 1315 (Oct. 22, 1991), pp. 61-70).
One problem with eliminating ghosting in a stereoscopic image is that ghosting subtraction techniques specified above are limited in situations where ghosting cannot be completely subtracted in all portions of the image. Some methods are able to remove ghosting, but the original image is modified more than a viewer may find acceptable, as compared to leaving some ghosting artifacts in the image. For example, if only ghosting subtraction methods are applied, an adequate amount of image brightness in a dark area of the image is needed to subtract light in the area where ghosting occurs. Modifying an image by applying a fixed amount of brightness globally can remove ghosting by subtraction, but overall image contrast may be negatively impacted. Another approach is to balance the amount of overall image brightness offset with the amount of ghosting removed. In general, conventional approaches are applied globally to the image and are not particularly effective for displayed 3D images having a wide dynamic range of ghosting. Ghosting removal can be problematic when an image includes several regions that do not require any offset in brightness to subtract ghosting and includes many regions that require a significant amount of brightness offset to subtract ghosting. Such images may contain a combination of regions that are impacted by bright daylight and regions that are in dark shade.
Accordingly, approaches that overcome the limitations described above are desirable that can minimize original image modification and maximize perceived ghosting reduction.